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      Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy.

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          Abstract

          Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy.

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          Author and article information

          Journal
          Epilepsy Behav
          Epilepsy & behavior : E&B
          1525-5069
          1525-5050
          Aug 2014
          : 37
          Affiliations
          [1 ] Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
          [2 ] Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA; Psychiatry Department of Clinics Hospital of School of Medicine of University of Sao Paulo, Brazil.
          [3 ] Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
          [4 ] Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA; Department of Neuropediatrics and Department of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Christian-Albrechts-University, Kiel, Germany.
          [5 ] Department of Health Informatics, University of San Francisco School of Nursing and Health Professions, San Francisco, CA, USA.
          [6 ] Edward B. Bromfield Epilepsy Center, Dept. of Neurology, Brigham and Women's Hospital, Boston, MA, USA; Institute of Sports Medicine, Department of Exercise and Health, Faculty of Science, University of Paderborn, Germany; Institute of Sports Medicine, Faculty of Science, University of Paderborn, Warburger Str. 100, 33098 Paderborn, Germany.
          [7 ] Department of Neurology, Harvard Medical School, Boston, MA, USA.
          [8 ] Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA. Electronic address: tobias.loddenkemper@childrens.harvard.edu.
          Article
          S1525-5050(14)00229-7
          10.1016/j.yebeh.2014.06.023
          25174001
          897a40be-50ef-451b-86b0-7a8174652b20
          Copyright © 2014. Published by Elsevier Inc.

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